Method and device for generating at least one virtual image of a measurement object

ABSTRACT

The invention relates to a method and a device for generating at least one virtual image of a measurement object, in which a virtual position and/or a virtual orientation of the measurement object is determined and a virtual position and/or virtual orientation of at least one imaging or image recording device of a coordinate measuring machine is determined. The virtual image is generated on the basis of geometric data of the measurement object and on the basis of optical properties of the measurement object and the virtual image is additionally generated on the basis of imaging parameters of the imaging or image recording device.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a National Stage application, under 35 U.S.C. §371,of International Application PCT/EP2014/060824, filed May 26, 2014,which designated the United States; this application also claims thepriority, under 35U.S.C. §119, of German Patent Application DE 10 2013209 770.0, filed May 27, 2013; the prior applications are herewithincorporated by reference in their entirety.

BACKGROUND OF THE INVENTION FIELD OF THE INVENTION

The invention relates to a method and device for generating at least onevirtual image of a measurement object which is intended to be measuredby a coordinate measurement machine.

Coordinate measurement machines are known which optically measuremeasurement objects, for example workpieces to be measured. To this end,such coordinate measuring machines include at least one imaging deviceby means of which it is possible to generate an image of the measurementobject, geometric dimensions being determined on the basis of the image,for example.

Thus, DE 202 21 476 U1 describes an optical precision measurementinstrument which comprises at least one image recording device and anassociated image processing device. It is set forth in the publicationthat image information relating to synthetic generation of image scenesthrough simulation can be obtained in order to maximize detectionstability while detecting edges and to minimize positional deviationwhile determining the position of an edge. This can necessitateknowledge about the reflection and transmission properties of thematerials, the type of edge transition and the illumination conditions.It is possible to simulate image information relating to methods ofcomputer simulation.

DE 10 2010 000 473 A1 describes a method for correcting projection datafor CT reconstruction by means of a CT detector with pixels. In thiscase, a workpiece can be measured by means of a CT measurement. Thedocument discloses that it is possible with the aid of simulation ofimaging, preferably by simulation of beam weakening, scattering and/ordetector sensitivity, to determine, from workpiece data, the requiredbeam energies required for the respective orientation positions so thatthe radiographic images achieve an evaluable contrast.

DE 103 27 019 A1 describes a method for determining an imaging qualityof an optical imaging system. So-called Zernike coefficients are used inthis case to describe imaging quality.

For a desired measurement, in particular for a peak measurement, of ameasurement object by a coordinate measurement machine, more or lesscomplex test plans are generally made. They include, for example,information relating to a path along which, for example, a tactile oroptical sensor of the coordinate measuring machine is to be movedrelative to the measurement object during the measurement.

As a rule, such test plans can be devised in the case of the opticalmeasurement only when the imaging device of the coordinate measurementmachine is simultaneously operated, since decisions relating to thequality of a test plan can be made only on the basis of the generatedimages.

It is generally also necessary when training to operate such acoordinate measurement machine to operate the imaging device, since thedesired training effect can be attained only on the basis of thegenerated images. However, it is disadvantageous in this case that inthese circumstances only one person respectively can be trained in usinga coordinate measuring machine, or there is a need to train more thanone person on a coordinate measuring machine.

This results in the technical problem of providing a method and a devicewhich enable processes which are based on images of an imaging device ofa coordinate measuring machine to be carried out even without operatingthe imaging device, the processes being impaired in quality as little aspossible.

It is a fundamental concept of the invention for an image generated bythe imaging device of a coordinate measuring machine to be simulated asrealistically as possible. During the simulation, the aim in this caseis, in particular, to take account as realistically as possible ofimaging properties of the imaging device and of the optical elementsassigned to it, optical properties of the workpiece and illuminationconditions.

BRIEF SUMMARY OF THE INVENTION

A method for generating at least one virtual image of a measurementobject is proposed. Here, the measurement object denotes a measurementobject which is to be measured by a coordinate measurement machine, inparticular in optical fashion. The virtual image in this case simulatesa real image generated by at least one imaging device of the coordinatemeasuring machine of a measurement object which is intended to bemeasured by the coordinate measuring machine.

In this process, a virtual position and/or virtual orientation of themeasurement object is determined. The virtual position and/ororientation can be determined here in a virtual reference coordinatesystem. The virtual position and/or orientation can be determined, inparticular, as a function of an actual position and/or orientation ofthe measurement object in the case of an actual measurement. The actualposition and/or orientation can be determined in this case in a realreference coordinate system, for example in a machine coordinate system.In this case, the virtual position and/or orientation can be determinedby a transformation of the actual position and/or orientation into thevirtual reference coordinate system.

Also determined is a virtual position and/or virtual orientation of atleast one imaging device of the coordinate measurement machine. Thistoo, can be formed with reference to the virtual reference coordinatesystem. The virtual position and/or orientation of the imaging devicecan be determined, in particular, as a function of an actual positionand/or orientation of the imaging device in the case of an actualmeasurement.

The virtual reference coordinate system can be, for example, a fixedcoordinate system based on the imaging device.

The virtual image is also generated as a function of geometric data ofthe measurement object and as a function of optical properties of themeasurement object. In this case, the virtual image is also determinedas a function of the previously explained virtual positions and/ororientations.

Geometric data of the measurement object can, for example, be determinedfrom CAD data (Computer aided design data). By way of example, it ispossible as a function of the geometric data to determine a spatialconfiguration, in particular an arrangement, a topography and/or aprofile of a surface, or of a plurality of regions of the surface of themeasurement object. The geometric data may thus permit description andrepresentation of the measurement object in the virtual referencecoordinate system.

Optical properties of the measurement object in this case denoteproperties of the measurement object which influence electromagneticradiation, in particular light, in particular also light in the visiblewavelength region. For example, and not exclusively, the opticalproperties comprise transparency, reflection properties, scatteringproperties, diffraction properties, transmission properties, refractionproperties, polarization properties, a texture and/or further propertieswhich influence an interaction of the measurement object with light. Theoptical properties thereby permit a description of how the measurementobjects emits radiation which can be used to generate images. In otherwords, it is possible thereby to describe the measurement object in theform of a radiometric source model. Here, the source model can alsoinclude a description of an illumination of the measurement object, forexample as a function of the position and/or orientation and/or emissionparameters of at least one light source, which are to be explained inmore detail below. In this case, the source model combines the opticalproperties of the measurement object and the illumination properties. Itis thereby possible to use the illumination model to simulate theemission characteristic resulting from specific illumination properties.

It is possible to determine the optical properties as a function ofmaterial properties of the measurement object. In this case, materialproperties include, for example, and once again not exclusively, asurface quality, a roughness, a color, a degree of luminosity, adensity, a proportion and/or a distribution of an element in a materialcomposition, structural properties and/or further material propertieswhich describe the material interacting with the light, and theconstruction thereof.

It is also possible to determine the optical properties as a function ofthe geometric properties explained previously. For example, opticalproperties can be determined as a function of a topography of a surfaceof the measurement object.

The previously explained optical properties, material properties andgeometric properties can be determined, in particular, for the regionsor sections of the measurement object which interact with light duringoptical measurement, in particular for a surface or partial surfaces ofa surface of the measurement object.

It is, of course, also possible to generate the virtual image as afunction of optical properties of a measurement environment. Saidoptical properties correspond to the optical properties previouslyattributed to the measurement object, and relate to an environment ofthe measurement object. It is thereby possible, for example, to considerwhether mist is present in a measurement environment.

According to the invention, the virtual image is additionally generatedas a function of imaging parameters of the imaging device. Imagingparameters describe how an object arranged in a range of acquisition ofthe imaging device is imaged as a function of its spatial positionand/or orientation, for example onto an image sensor. As explained belowin more detail, this can also include the generation of electricalsignals which represent the image. By way of example and notexclusively, in this case imaging parameters include an aperture,magnification or demagnification, an aspect ratio, a projection mode, anaperture angle, optical properties of the imaging device such as, forexample, diffraction, scattering, refraction and polarizationproperties, a focal length, a quality of the antireflection coating,distortion properties, resolution of an image sensor, conversionproperties of the image sensor with reference to the conversion of lightinto electrical signals (sensor parameters) and further properties whichdescribe the generation of electrical signals and signals representingthe image by the imaging device. As a function of imaging parameters, itis also possible to describe effects such as, for example lensreflections, distortions, a depth of focus, a chromatic aberration,aspheric lens refraction and so-called bokeh effects which occur duringimaging.

The term imaging device in this case may also include optical elementsfor imaging, for example lenses, objectives, mirrors and further opticalelements for beam guidance which are involved in the generation of theimage by the imaging device. The imaging parameters thus also includethe imaging parameters of the optical elements, in particularaberrations of an objective.

Imaging parameters can, for example, be described by so-called Zernikecoefficients and/or by a point-spread function. Zernike coefficients inthis case denote coefficients of a power series function for describingaberrations in imaging devices with reference to a measuring axis which,for example, can be an optical axis of the imaging device. Such Zernikecoefficients are described in DE 103 27 019 A1 as a characteristicnumber for describing an image quality. Imaging parameters can also bedependent on wavelength, imaging parameters being determined as afunction of wavelength.

Depending on the previously explained virtual positions and/ororientations of the measurement object and of the imaging device, it isthen possible to determine a virtual position and/or orientation of themeasurement object in the range of acquisition of the imaging device. Itis therefore also possible to determine a working distance from themeasurement object to the imaging device and/or to an optical element ofthe imaging device. It is also possible to determine a viewing angle anda profile of an optical axis relative to the measurement object.

The proposed method advantageously permits the generation of a virtualimage which corresponds as accurately as possible to the actuallygenerated image. The virtual image can be generated in this case in theform of electrical signals, for example in the form of bits, theelectrical signals deviating as little as possible from electricalsignals which are generated in the generation of an actual image. Forexample, the virtual image can be generated in such a way that adifference between amplitudes and/or a distribution of the electricalsignals which represent the virtual image, and amplitudes and/or adistribution of the electrical signals which represent the correspondingactual image is smaller than a predetermined measure. By way of example,the previously explained optical properties, material properties andimaging parameters can be determined in such a way that the previouslyexplained difference is smaller than the predetermined measure, forexample for one or more of the reference images. As with actuallygenerated images, the electrical signals can in this case encode orrepresent gray values of gray scale pictures, or color values of colorimages.

The generation of virtual images which correspond as accurately aspossible to the corresponding actually generated images advantageouslypermits applications which are carried out as a function of images ofthe imaging device, also to be capable of being carried out withoutactual generation and therefore without actual operation of the imagingdevice. For example, a test plan can be devised and tested even withoutactual operation of the imaging device. In turn, this enables improvedoperation of the coordinate measuring machine, since applications, forexample the test plans mentioned above, can be tested and optimizedbefore operation, that is to say offline. For example, methods of imageprocessing which are used to determine geometric dimensions of themeasurement object, for example methods for edge detection, can also betested and optimized as a function of virtual images. An actualmeasurement can then be performed in accordance with the test plans thusoptimized.

In a further embodiment, a virtual position and/or virtual orientationof at least one light source is determined, the virtual imageadditionally being determined as a function of emission parameters ofthe light source. The virtual image can also be determined as a functionof the virtual position and/or orientation of at least one light source.

The imaging is also dependent on prevailing illumination conditionsduring an actual measurement operation. Determination of the virtualposition and/or orientation, for example in the previously explainedvirtual reference coordinate system, also enables the determination ofthe virtual position and/or orientation of the illumination sourcerelative to the measurement object and to the imaging device. As isexplained below in more detail, it is also possible to optimize avirtual position and/or orientation of the illumination source relativeto the measurement object.

It is possible that a virtual position and/or orientation of the lightsource corresponds to the virtual position and/or orientation of theimaging device or can be determined as a function thereof, in particularwhen the actual light source is arranged fixed relative to the imagingdevice. For example, the light source can be connected in a mechanicallyrigid manner to the imaging device and can form a structural unit withthe latter.

Emission parameters of the light source describe the emission of lightby the light source. Emission parameters include, for example and notexclusively, an intensity, a wavelength or a spectral distribution ofthe emitted light, a spatial distribution of the emitted light, apolarization and a (main) beam direction of the emitted light and/orfurther emission parameters.

The number of the light sources actually present is already known for acoordinate measurement machine. Likewise, the position and/ororientation of the light sources actually present, for example relativeto the imaging device, and their emission parameters are already known.The emission parameters can also, for example, be parameters which auser can adjust semi-automatically or fully automatically. Consequently,the virtual position and/or orientation and the emission parameters canbe determined from said information already known.

For example, such a light source can be configured as a so-called ringlight with a plurality of component light sources, which spatiallyincludes at least part of the imaging device, for example an objective.A division or segmentation of the individual component light sources mayalready be known for such a ring light. This therefore also permitsdetermination of the direction of irradiation of the ring light.

The quality of the generation of the virtual image can advantageously befurther improved as a function of the emission parameters. Inparticular, so-called ray tracing methods can be applied as a functionof the position and/or orientation and of the emission parameters. Saidray-tracing method is used to determine the calculation of a spatialprofile of a light beam and the properties thereof along the spatialprofile, the light beam being oriented from the measurement object orfrom the light source to the measuring device via the measurementobject. This can be performed in particular, as a function of thepreviously explained spatial position and/or orientation of themeasurement object, the imaging device, as a function of the opticalproperties, material properties and geometric properties of themeasurement object, and as a function of the imaging properties of theimaging device. It is thereby possible to determine the calculation ofan interaction which the measurement object and the imaging device exerton light beams emitted by at least one light source, and the changes,resulting therefrom, of properties of the light beams. That is to say,the simulation of the image generation is thereby improved.

Again, so-called rendering methods can be applied as a function of theposition and/or orientation and of the emission parameters. In therendering method, a spatial profile of a light beam and the propertiesthereof along the spatial profile are determined by calculation, thelight beam being oriented from the imaging device to the measurementobject or via the measurement object to the light source. Consequently,a measurement object is simulated such as it radiates in the case of aprescribed illumination. For example, it is possible in the renderingmethod to evaluate a so-called bidirectional reflection function and alight emission function for various wavelengths.

Thus, light beam propagation is calculated in both the ray-tracingmethod and rendering method, but with opposed directions of propagation.Here, the rendering method is generally more efficient since, forexample, scattering and overillumination effects of the measurementfield are considered only partially or not at all.

It is also possible, as a function of the virtual position and/ororientation of the at least one light source and of the emissionparameters to determine whether a virtual direct-light image, a virtualtransmitted-light image, a virtual bright image, a virtual dark image ora mixture of said image types is generated.

In a further embodiment, the imaging parameters of the imaging devicecomprise imaging parameters of at least one optical element of theimaging device. As previously explained, the imaging device can includeoptical elements for beam guidance, for example lenses, objectives ormirrors. These also influence properties of light beams which areconverted into electrical signals to generate the image of themeasurement object.

Consequently, the quality of the virtual image is further improved bytaking account of imaging parameters of the optical elements.

In a further embodiment, the virtual position and/or virtual orientationof the measurement object and/or of the at least one imaging deviceare/is determined as a function of virtual motion parameters of at leastone movable part of the coordinate measurement machine and/or as afunction of geometric data of the coordinate measurement machine.

It is thereby advantageously possible to take account of a changingrelative position and/or orientation between the measurement object andimaging device during an actual measurement, and/or of fixedly arrangedparts of the coordinate measuring machine.

For example, the imaging device and/or the measurement object can bemoved during measurement by at least one movable part of the coordinatemeasuring machine, in order to acquire different regions of themeasurement object optically. In this case, however, there is also achange in the relative position and/or orientation, and thus in aprofile and properties of the light beams which are converted intoelectrical signals in order to generate the image of the measurementobject. The change in the relative position and/or orientation can bedetermined as a function of the virtual motion parameters of thecoordinate measuring machine and, if appropriate, the spatialconfiguration of the coordinate measuring machine.

In addition to the geometric data of the workpiece previously explained,the optical properties of the workpiece and the imaging properties ofthe imaging device, the virtual image can also be generated as afunction of geometric data of the coordinate measuring machine. Takinggeometric data of the coordinate measuring machine into accountadvantageously enables an influence on movable and/or fixedly arrangedparts of the coordinate measuring machine on the imaging of themeasurement object, for example a shading or occlusion to also be takeninto account.

The geometric data can be determined, for example, as a function of CADdata of the coordinate measuring machine. Geometric data can, inparticular, also be determined as a function of movable axes, a positionof rotary and/or swivel joints, and/or a position of a turntable of thecoordinate measuring machine. It is also possible to determine amagnitude, a position and/or an orientation of a measurement volume ofthe coordinate measuring machine. This advantageously enables therestriction of a region which is really only relevant while generatingvirtual images. Thus, it is possible, for example, to determine partsand/or features of the measurement object which are arranged in themeasurement volume and are therefore really only capable of beingimaged. Also, interfering contours, for example contours of thecoordinate measuring machine, which prevent or interfere with thegeneration of an image can be determined.

The relative spatial position and/or orientation of the imaging deviceto the measurement object in the virtual coordinate system can bedetermined as a function of motion parameters of movable parts, forexample as a function of desired signals for actuators of the coordinatemeasuring machine. For this purpose, there may be a need for kinematicdescription of the coordinate measuring machine which enables aso-called forward calculation. The kinematic description can beperformed in this case as a function of the actual geometricconfiguration or geometric data of the coordinate measuring machine, forexample in the form of a function or in the form of transformationmatrices.

This advantageously enables the generation of a plurality of virtualimages which correspond to actual images which are generated at variouspositions along a path of the imaging device during measurement, itbeing possible to describe the path as a function of motion parametersof the movable parts. Thus, for example, it is conceivable to determineappropriate motion parameters as a function of a planned path, and thento determine a virtual image as a function of motion parameters forvarious relative positions and/or orientations along the path, aspreviously described. The quality of the desired path can then, in turn,be checked as a function of the generated virtual images. This thereforeenables the qualitative checking of test plans without the need tooperate the coordinate measuring machine. The checking can be carriedout as a function of desired signals, as a result of which an idealized,error-free movement of the movable parts of the coordinate measuringmachine is simulated. Alternatively, it is also possible during themovement to take account of already known correction data which describeknown deviations from the error-free movement, for example rotation,tilting, rolling or a transverse movement of the movable parts of thecoordinate measuring machine.

In a further embodiment, the virtual image is additionally determined asa function of sensor parameters of an image sensor of the imagingdevice.

Here, the image sensor denotes a means for converting electromagneticradiation, in particular light, into electrical signals. Said means can,in turn, be converted into bits or bit sequences, said bits and bitsequences encoding information of an image. For example, the imagesensor can be a CCD sensor or a CMOS sensor. Of course, other types ofimage sensors are also conceivable.

The above-described conversion is dependent here on sensor parameters.The latter describe, for example, a relationship between the intensityof the lights and, for example, an amplitude of the electrical signal.Again, sensor parameters can describe noise properties of the imagesensor, for example in the form of a signal-to-noise ratio. Furthermore,said sensor parameters can describe a resolution, for example in theform of a pixel size, a chip size, control characteristics and dynamicproperties. Dynamic properties can, for example, include properties of aphotocurrent which is generated or released on an exposure of the imagesensor with a predetermined intensity, a minimum or maximum exposuretime and/or properties, for example nonlinearities, a signal conversionof light into electrons and then into bits.

It is also possible for sensor parameters to describe a reflectivity ofthe image sensor. The reflectivity can, for example, be dependent on adirection of irradiation. Consequently, reflectivity of the imagesensor, which can, for example, generate so-called false light in thecase of actual imaging, can also be taken into account directly orindirectly in the generation of the virtual image.

As a result, actual properties of the image sensor which affect thegeneration of an actual image can advantageously also be taken intoaccount in the generation of a virtual image. This, in turn,advantageously permits an improvement in the quality of the virtualimages generated in such a way that the latter deviate as little aspossible from the corresponding actual images.

In a further embodiment, after generation of the virtual image at leastone image processing method is applied to the virtual image, the imageprocessing method simulating at least one aberration of the imagingdevice. The image processing method can be applied here to at least onepixel or a predetermined region of pixels. Here the simulation ofaberrations is therefore performed not as a function of a description bymeans of imaging parameters, but by the application of an imageprocessing method. Therefore no model-based generation of a virtualimage but rather an event-based generation of a virtual image isperformed.

The image processing method in this case denotes, for example, amathematical operation which is applied to a value-based representationof the virtual image. By way of example, value-based means in this casethat the mathematical operations take account of and/or vary intensityvalues, for example gray scale values, of pixels.

Such image processing methods include, for example, smoothingoperations, filter operations and further operations for varying theintensity values of pixels. Again, such image processing methods can beused to simulate an effect, which can also be denoted as so-calledcrosstalk, passing from sensor elements, adjacent to a sensor element,of the image sensor onto said sensor element, which can arise in theevent of an exposure and falsify the signal generated by the sensorelement.

Consequently, it is advantageously possible to simulate imagingproperties of adequate accuracy which could only be described withdifficulty in a model-based fashion, in particular mathematically.

In a further embodiment, after generation of the virtual image at leastone smoothing filter operation is applied to the virtual image. Astrength of the smoothing filter operation is selected as a function ofa distance of a point, imaged in one or more pixels, on the measurementobject, from a focal plane of the imaging device. Here, a strength ofthe smoothing filter operation rises with the increasing distance of theimaged point from the focal plane. Said distance can, for example, bedescribed as a function on the imaging properties of the imaging device.In ray-tracing methods, said distance can also be determined during thecalculation of an optical path and stored. The smoothing filteroperation can be applied in this case to the pixel or the pixels inwhich the corresponding point has been imaged.

The smoothing operation can, for example, comprise an averaging, inparticular even a weighted averaging, a mean value of intensity valuesbeing calculated in a predetermined region of pixels. The predeterminedregion can in this case include the pixel or the pixels in which thecorresponding point has been imaged. In this case, a magnitude of thepredetermined region can be selected as a function of a strength. Inparticular, the region can become greater with rising strength.

Thus, for example, an intensity value of a pixel which images a pointfrom the focal plane cannot be changed. A pixel which images a point farremoved from the focal plane can be strongly blurred with adjacentpixels.

This advantageously enables a simple simulation of a depth of focuseffect which brings about the previously explained effect in thegeneration of pixels of actual images. However, this is not performed inmodel-based fashion, but rather the proposed smoothing filter operationgenerates results which match the depth of focus effect. This isadvantageous in particular when the previously explained ray-tracingmethod or rendering method is used, since said methods generate sharpvirtual images.

Since the numerical aperture of the imaging device influences the depthof focus effect decisively, as previously explained said effect can,however, alternatively be simulated in the generation of the virtualimage by taking account of the numerical aperture for determining thevirtual image.

In a further embodiment, a (virtual) focal plane of the imaging deviceis determined, the virtual image corresponding to the part of thevirtual measurement object arranged in the (virtual) focal plane. Thismeans that in the generation of the virtual image account is takenexclusively of information from the (virtual) focal plane or from apredetermined region about said (virtual) focal plane. Consequently, itis only for the parts or regions of the virtual measurement object whichare arranged in the (virtual) focal plane or in a region ofpredetermined magnitude about the focal plane that it is determined howthe latter are imaged in a virtual image plane, or how said beamsimaging parts or regions are converted into electrical signals.

In particular, a ray-tracing method or rendering method can be carriedout exclusively for the parts or regions of the measurement object whichare arranged in the (virtual) focal plane or in predetermined regionabout said focal plane. For example, the selection of the previouslyexplained parts or regions can be performed by a so-called clippingfunction which permits the selection of specific depth regions duringthe ray-tracing method.

The generation of a virtual image can be simplified hereby in anadvantageous way, in particular be accelerated, since less informationneed be taken into account by generating the virtual image.

In a further embodiment, at least one adjustable parameter of the atleast one light source is adjusted as a function of a correspondingparameter in order to generate the virtual image. If the generation ofthe virtual image is, for example, carried out as a function of specificemission parameters of the at least one light source it is, for example,possible to adjust a variable parameter of the actual light source inaccordance with the corresponding emission parameter. For example, anintensity of an actual light source can be adjusted in accordance withan intensity of the light source which is used in the generation of thevirtual image. Alternatively or cumulatively, it is also possible forother ones of the previously explained emission parameters to beappropriately adjusted in the case of the actual light source.

Alternatively or cumulatively, at least one adjustable parameter of thecoordinate measuring machine can be adjusted in accordance with theparameter taken into account in the generation of the virtual image.This holds true, in particular, for the previously explained motionparameters.

Alternatively or cumulatively, at least one adjustable parameter of theimaging device can be adjusted in accordance with the parameter takeninto account in generating the virtual image. Such a parameter can be afocal length, for example.

Alternatively or cumulatively, at least one adjustable parameter of theoptical sensor can be adjusted in accordance with the parameter takeninto account in generating the virtual image. Such a parameter can be asensitivity, for example.

This therefore advantageously enables the parameters used for simulationto be adopted for adjusting actual parameters, and thus for controllingan actual optical measurement. The adoption can be performedautomatically in this case, or be initiated by an appropriate userinput, for example. For this purpose, appropriate data can betransmitted from a device for generating the at least one virtual imageto one or more appropriate control devices of the coordinate measuringmachine.

The proposed method advantageously enables the realistic simulation of arecording of an image by an imaging device of a coordinate measuringmachine. As the image is being recorded, a user or else an algorithm forautomatic adjustment can assess an image section, a suitablemagnification, a suitable working distance and further adjustableparameters, for example as a function of virtual images, generated inthis way, for the actual optical measurement of a workpiece. Parametersused for the simulation can then be used to control the coordinatemeasuring machine.

Again, methods for detecting and determining features and for focusmeasurement can be tested as a function of the virtual images generated.By way of example, it is thus possible to prepare a test plan whichenables a desired measurement of the measurement object before theactual measurement, that is to say offline.

Furthermore, the proposed method can also be used to test methods forevaluating actually generated images, for example methods forimage-based measurement of measurement objects. For example, methods, inparticular also image processing methods, for feature detection, edgedetection and edge measurement can be carried out as a function of thevirtual images.

A user can also generate virtual images with various parameters, forexample with various illumination intensities, with various motionparameters, with various virtual positions and/or orientations etc., andcan use the virtual images generated in order to determine the optimumparameters for a measurement actually used. This can be performedindividually for each measurement task, that is to say for eachmeasurement object, or even for one, several or all feature(s) or(partial) structures to be measured on a measurement object.

Again, it is possible to optimize results of the previously explainedmethods for evaluation as a function of the virtual images. Here,parameters which are used to generate the virtual images and whichcorrespond to appropriate, adjustable parameters for an actualmeasurement can be varied in such a way that results are optimized. Anoptimum result can be obtained, for example, if a deviation of a result,for example a geometric dimension, a method for evaluating a realresult, for example a real dimension, is minimum. For example, emissionparameters, adjustable in this way, of a light source, adjustable motionparameters of the coordinate measuring machine, adjustable imagingproperties of the imaging device and relative positions and/ororientations of the measurement object and/or of the at least one lightsource and/or of the at least one imaging device can be determinedrelative to one another so as to enable as accurate an opticalmeasurement of a measurement object as possible.

By way of example, the determination of parameters that are optimum inthis way can be performed here by iteration or by parameter optimizationmethods, virtual images being used to determine the optimum parameters.For example, known methods for determining optimum parameters which useimages actually generated can be used to determine appropriate optimumparameters as a function of the virtual images.

Of course, the determination of the optimum parameters, in particular ofoptimum emission parameters can be carried out manually,semi-automatically or else fully automatically.

It is also possible to run through parts of the sequence. For example,it is possible to determine only optimum, adjustable parameters, forexample an intensity, of at least one light source or only optimum,adjustable parameters, for example a focus, of the imaging device.

Again, CAD data of a desired measurement object to be measured can beread in and the proposed generation of virtual images can therefore becarried out for each desired measurement object. Consequently,appropriate demonstration of the mode of operation of a predetermined,coordinate measurement machine for optical measurement, for example, canbe performed directly for a customer, the imaging properties and, ifappropriate, the emission properties of light sources of thepredetermined coordinate measuring machine being known.

The method also advantageously enables the determination of optimumadjustable parameters of a plurality of coordinate measurement machines,for example a plurality of coordinate measurement machines of a seriesby means of which for example the same or similar measurement objectsare to be measured. For this purpose, virtual images with normalizedadjustable parameters can be generated. In particular, normalizedadjustable parameters can be determined in such a way that, aspreviously explained, a measurement result is optimized.

It is then possible as a function of the normalized parametersdetermined by the optimization, to determine, for each of the pluralityof coordinate measuring machines, corresponding parameters which areadjusted for the actual measurement. In this case, a relationshipbetween the normalized parameters and parameters actually be adjustedmay be known in advance for each coordinate measuring machine. Saidrelationship can, for example, be determined by determining parametersactually to be adjusted for each coordinate measuring machine, forexample in a calibration method, in such a way that the same measurementresult is attained. Said parameter set then forms a reference parameterset, specific to a measuring device, for normalized parameters. Forexample, normalized parameters can be specified relative to thereference parameter set.

By way of example, adjustable parameters for each light source or eachgroup of a plurality of light sources of each coordinate measurementmachine can be determined in such a way that a reference intensity isgenerated in the case of which an illuminated reference object generatesa predetermined illumination, for example 95%, of the image sensor ofthe imaging device. For example, the reference object can be a white,diffusely reflecting object with a predetermined reflectivity of, forexample, 50%, in particular a ceramic disk. Said parameters form thereference parameter set for the respective coordinate measuring machine.

A virtual image can then be determined as a function of said intensityand/or of a predetermined percentage of said reference intensity. By wayof example, if an intensity which amounts only to a portion of thereference intensity is determined as the optimum intensity, it is thenpossible to determine the corresponding parameters for a coordinatemeasuring machine in such a way that only the corresponding proportionis generated. In particular, it is also possible to carry out theoptimization previously explained, the proportion of the referenceintensity being changed.

The determination of virtual images as a function of proportions of thereference intensity advantageously does not necessarily require arenewed calculation of the beam propagation by ray-tracing or renderingmethods, since intensities of the virtual image which have beendetermined as a function of the reference intensity can be scaled onlyin accordance with the predetermined proportion. Said approximation isall the is better the less the further emission parameters such as, forexample, beam angle, spectrum, average wavelength and polarizationdepend on the intensity.

This advantageously enables the determination of adjustable parametersfor an optimum test plan by only one simulation or a simulation scenarioand a corresponding transfer to a plurality of similar coordinatemeasuring machines.

Also described is a computer program product in or on which a code forexecuting one of the above explained methods is stored. In particular,the computer program product can include a computer program which hassoftware means for carrying out one of the above explained methods, whenthe computer program is executed in an automation system.

In a further embodiment, a measurement accuracy of a coordinatemeasuring machine, in particular the accuracy of the optical measurementof a measurement object carried out by the coordinate measuring machineis determined as a function of the virtual image. For example, at leastone geometric property of the measurement object which can be determinedas a function of the previously known geometric data of the measurementobject can be compared with a corresponding geometric property,determined in an image-based fashion, which is determined as a functionof the virtual image. A comparison can, for example, be performed byforming the difference between the geometric property and the geometricproperty determined in an image-based fashion. The measurement accuracycan then be determined as a function of the comparison or of thedifference.

A geometric property can in this case include structural sizes of(partial) structures of the measurement object, by way of example andnot exclusively, a width, a length, a depth, a diameter, an area, alocation or position, an orientation of a (partial) structure of themeasurement object. The (partial) structure can be a line, an edge, anopening, for example.

This advantageously enables a measurement accuracy which is achievedwith a test plan, for example, to be assessed before actually carryingout the test plan.

Again, it is thus possible to determine an influence on the measurementaccuracy of a change in one or more, in particular adjustableparameters. This can also be denoted as parameter-dependent sensitivity.

In a further embodiment, a measurement accuracy of various methods forimage-based measurement of a measurement object is compared as afunction of the virtual image.

The previously explained image-based determination of geometricproperties from a virtual or actual image of the measurement object isperformed at least partially by image processing methods. By way ofexample, it is possible here to apply methods for structural detection,for example detection of edges or lines. Again, it is possible to applymethods for image improvement, for example filter methods for noisereduction. It is also possible to apply methods for determining a pixelposition and a distance between various pixels. If an appropriateconversion factor or an appropriate conversion rule is known, it isthereby possible to convert these properties determined in animage-based fashion, that is to say, for example, positions, distances,orientations into corresponding, actual properties.

If there exists a plurality of image processing methods which can becarried out alternatively or cumulatively for the purpose of image-baseddetermination of geometric properties, then it is possible to comparethe geometric properties determined as a function of a first imageprocessing method or of a first sequence of various image processingmethods with geometric properties which have been determined as afunction of a further image processing method or a further sequence ofvarious image processing methods. This is possible because the samevirtual image is used as raw image for the compared image processingmethods and/or sequences of image processing methods.

Again, as previously explained, the geometric properties determined withthe various image processing methods can be compared with correspondinggeometric properties which can be determined as a function of thealready known geometric data of the measurement object.

Consequently, it is advantageously possible to compare the various imageprocessing methods or sequences for the same set of, in particularadjustable, parameters. Thus it is possible, in particular, to select animage processing method or a sequence which has the highest measurementaccuracy for the set of parameters.

Again, it is thereby possible to determine an influence of a variationof one or more, in particular adjustable parameters of the coordinatemeasurement machine and/or of the light source and/or of the imagingdevice on the measurement accuracy of various image processing methodsor sequences of image processing methods. Consequently, it is possibleby way of example to switch over between various image processingmethods or various sequences of image processing methods when parameterschange. In particular, it is possible to switch over between variousimage processing methods or various sequences of image processingmethods so as respectively to select for a current set of parameters theimage processing methods or sequence of image processing methods, themeasurement of which accuracy is highest for the current set ofparameters. The method or sequence selected in such a way can then alsobe applied in a corresponding actual measurement operation.

Also proposed is a device for generating at least one virtual image of ameasurement object, the device including at least one control andevaluation device, it being possible to use the control and evaluationdevice to determine a virtual position and/or virtual orientation of themeasurement object, and a virtual position and/or virtual orientation ofat least one imaging device of the coordinate measurement machine, itbeing possible to generate the virtual image as a function of geometricdata of the measurement object and as a function of optical propertiesof the measurement object.

According to the invention, the virtual image can additionally begenerated as a function of imaging parameters of the imaging device. Thecontrol and evaluation device can be appropriately configured for thispurpose.

The proposed coordinate measurement machine advantageously enables oneof the methods explained above to be carried out.

Here, the evaluation and control device can be connected by signaling ordata processing to further control devices of the coordinate measurementmachine. In this case, parameters of the control and evaluation devicewhich are used to generate the virtual image are transmitted to thefurther control devices, the further control devices adjusting, as afunction of the transmitted parameters, corresponding, adjustableparameters of the coordinate measurement machine and/or the at least onelight source and/or the imaging device. For this purpose, the parametersused to generate the virtual image are converted appropriately, forexample by means of an already known conversion rule.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

The invention is explained in more detail with the aid of an exemplaryembodiment. The sole FIGURE shows a schematic flowchart of a methodaccording to the invention.

DESCRIPTION OF THE INVENTION

In a first step S1, CAD data CAD_M of a measurement object to bemeasured are input. Material properties ME_M of the measurement objectto be measured are also input. These also include properties of asurface of the measurement object, for example a surface quality and adegree of gloss. Optical properties of the measurement object to bemeasured, in particular for various partial regions of the measurementobject, can be determined as a function of the material properties ME_Mand of the geometric properties determined from the CAD data CAD_M. Byway of example, optical properties of various materials and materialcompounds can be stored for this purpose in a memory device. Opticalproperties include, in particular, properties of reflection,transmission, diffraction and scattering for the measurement object.

In a second step S2, imaging parameters uAE, vAE of an imaging device,for example a camera, of the coordinate measurement machine are input.These include invariable imaging parameters uAE and variable imagingparameters vAE. Imaging parameters uAE, vAE in this case also includesensor parameters of an image sensor of the imaging device. Variableimaging parameters vAE in this case include, for example, a focallength, a working distance from the measurement object, a numericalaperture and telecentric properties.

In a third step S3, emission parameters uEP, vEP of all light sources ofthe coordinate measurement machine are input. These include, in turn,invariable emission parameters uEP and variable emission parameters vEP.Variable emission parameters vEP in this case include, for example, anintensity of the generated light, a wavelength, an on time and a turn-ontime.

In a fourth step S4, CAD data CAD_k and material properties ME_k of thecoordinate measurement machine are input. Motion parameters BP of thecoordinate measurement machine are also input. The motion parameters BPin this case include desired positions of drive devices, in particularlinear and/or rotary drive devices, of the coordinate measurementmachine, for example motion parameters BP of the movable axles andjoints of the coordinate measurement machine, and motion parameters BPof a turntable on which the measurement object to be measured isarranged for actual measurement.

In a fifth step S5, a relative position and/or orientation of thevirtual measurement object is determined in relation to the imagingdevice, and a relative position and/or orientation of the light sourcesis determined in relation to the virtual measurement object in a virtualreference coordinate system. For this purpose, it is possible todetermine a virtual position and/or orientation of the measurementobject, of the imaging device and of the light sources in the virtualreference coordinate system.

This determination of the virtual position and/or orientation of theimaging device and of the measurement object can be performed, forexample, as a function of the motion parameters BP of the coordinatemeasurement machine, and of the CAD data of the coordinate measurementmachine.

In a sixth step S6, a ray-tracing method or a rendering method, whichtakes account computationally of the previously input properties,determines a distribution of a beam intensity in a virtual image plane.The electrical signals which are generated by the optical sensor for thegiven distribution of the beam intensity can then be determined as afunction of the sensor parameters. Intensity variables, in particular inthe form of bits, of pixels of a virtual image vA can now be determinedby taking account, if appropriate, of further signal conversions.

In a seventh step S7, a smoothing filter operation is applied to pixelsof the virtual image vA, an intensity of the smoothing filter operationbeing selected as a function of distances of the points, which areimaged in said pixels, from a focal plane of the imaging device.

In an eighth step S8, known methods for evaluating images, for examplefor image-based measurement of optically imaged measurement objects arethen applied to the virtual image vA in order to determine geometricdimensions of the measurement object from which the virtual image vA hasbeen generated.

Said dimensions can be compared in a ninth step S9 to dimensions whichhave been determined as a function of the CAD data CAD_M of themeasurement object. It is then possible in a tenth step S10 to vary thevariable imaging properties vAE and emission parameters vEP and motionparameters BP of the coordinate measurement machine, and to carry outthe method again starting from the second step S2. By way of example,the variation can be performed in such a way that or until a differenceof the dimensions determined in the ninth step S9 is at a minimum orundershoots a predetermined measure.

The invention claimed is:
 1. A method for determining adjustableparameters of a plurality of coordinate measurement machines, the methodcomprising the following steps: generating at least one virtual image ofa measurement object; determining at least one of a virtual position ora virtual orientation of the measurement object; determining at leastone of a virtual position or a virtual orientation of at least oneimaging device of a coordinate measurement machine; generating thevirtual image as a function of geometric data of the measurement objectand as a function of optical properties of the measurement object;additionally generating the virtual image as a function of imagingparameters of the at least one imaging device; generating the virtualimage with normalized adjustable parameters; and determiningcorresponding parameters being adjustable for actual measurement foreach of the plurality of coordinate measurement machines as a functionof the normalized parameters.
 2. The method according to claim 1, whichfurther comprises determining at least one of a virtual position or avirtual orientation of at least one light source, and additionallydetermining the virtual image as a function of emission parameters ofthe at least one light source.
 3. The method according to claim 2, whichfurther comprises adjusting at least one adjustable parameter of atleast one of the at least one light source or the coordinate measurementmachine or the at least one imaging device as a function of acorresponding parameter used to generate the virtual image.
 4. Themethod according to claim 1, wherein the imaging parameters of the atleast one imaging device include imaging parameters of at least oneoptical element of the at least one imaging device.
 5. The methodaccording to claim 1, which further comprises determining at least oneof the virtual position or the virtual orientation of the measurementobject or of the at least one imaging device as a function of at leastone of virtual motion parameters of at least one movable part of thecoordinate measurement machine or as a function of geometric data of thecoordinate measurement machine.
 6. The method according to claim 1,which further comprises additionally determining the virtual image as afunction of sensor parameters of an image sensor of the at least oneimaging device.
 7. The method according to claim 1, which furthercomprises applying at least one image processing method to the virtualimage after generation of the virtual image, the image processing methodsimulating at least one aberration of the at least one imaging device.8. The method according to claim 7, which further comprises applying atleast one smoothing filter operation to the virtual image aftergeneration of the virtual image, and selecting a strength of the atleast one smoothing filter operation as a function of a distance of apoint, imaged in one or more pixels, on the measurement object, from afocal plane of the at least one imaging device.
 9. The method accordingto claim 1, which further comprises determining a focal plane of the atleast one imaging device, the virtual image corresponding to a part ofthe virtual measurement object disposed in the focal plane or in apredetermined region around the focal plane.
 10. The method according toclaim 1, which further comprises determining a measurement accuracy of acoordinate measuring machine as a function of the virtual image.
 11. Themethod according to claim 1, which further comprises comparing ameasurement accuracy of methods for image-based measurement of ameasurement object, as a function of the virtual image.
 12. Anon-transitory computer program product, comprising a code stored in oron the computer program product for carrying out a method according toclaim
 1. 13. A method for generating at least one virtual image of ameasurement object, the method comprising the following steps:determining at least one of a virtual position or a virtual orientationof the measurement object; determining at least one of a virtualposition or a virtual orientation of at least one imaging device of acoordinate measurement machine; generating the virtual image as afunction of geometric data of the measurement object and as a functionof optical properties of the measurement object; additionally generatingthe virtual image as a function of imaging parameters of the at leastone imaging device; and additionally determining the virtual image as afunction of sensor parameters of an image sensor of the imaging device.14. The method according to claim 13, which further comprisesdetermining at least one of a virtual position or a virtual orientationof at least one light source, and additionally determining the virtualimage as a function of emission parameters of the at least one lightsource.
 15. The method according to claim 14, which further comprisesadjusting at least one adjustable parameter of at least one of the atleast one light source or the coordinate measurement machine or the atleast one imaging device as a function of a corresponding parameter usedto generate the virtual image.
 16. The method according to claim 13,wherein the imaging parameters of the at least one imaging deviceinclude imaging parameters of at least one optical element of the atleast one imaging device.
 17. The method according to claim 13, whichfurther comprises determining at least one of the virtual position orthe virtual orientation of the measurement object or of the at least oneimaging device as a function of at least one of virtual motionparameters of at least one movable part of the coordinate measurementmachine or as a function of geometric data of the coordinate measurementmachine.
 18. The method according to claim 13, which further comprisesapplying at least one image processing method to the virtual image aftergeneration of the virtual image, the image processing method simulatingat least one aberration of the at least one imaging device.
 19. Themethod according to claim 18, which further comprises applying at leastone smoothing filter operation to the virtual image after generation ofthe virtual image, and selecting a strength of the at least onesmoothing filter operation as a function of a distance of a point,imaged in one or more pixels, on the measurement object, from a focalplane of the at least one imaging device.
 20. The method according toclaim 13, which further comprises determining a focal plane of the atleast one imaging device, the virtual image corresponding to a part ofthe virtual measurement object disposed in the focal plane or in apredetermined region around the focal plane.
 21. The method according toclaim 13, which further comprises determining a measurement accuracy ofa coordinate measuring machine as a function of the virtual image. 22.The method according to claim 13, which further comprises comparing ameasurement accuracy of methods for image-based measurement of ameasurement object, as a function of the virtual image.
 23. A device forgenerating at least one virtual image of a measurement object, thedevice comprising: at least one control and evaluation device configuredto determine at least one of a virtual position or a virtual orientationof the measurement object and at least one of a virtual position or avirtual orientation of at least one imaging device of a coordinatemeasurement machine; the measurement object having geometric data andoptical properties as a function of which the virtual image can begenerated; the at least one imaging device having imaging parameters asa function of which the virtual image can additionally be generated; andthe at least one imaging device having an image sensor with sensorparameters as a function of which the virtual image can additionally bedetermined.